Traffic grooming, routing, and wavelength assignment in WDM transport networks with sparse grooming resources

While a single fiber strand in wavelength division multiplexing (WDM) has over a terabit-per-second bandwidth and a wavelength channel has over a gigabit-per-second transmission speed, the network may still be required to support traffic requests at rates that are lower than the full wavelength capacity. To avoid assigning an entire lightpath to a small request, many researchers have looked at adding traffic grooming to the routing and wavelength assignment (RWA) problem. In this work, we consider the RWA problem with traffic grooming (GRWA) for mesh networks under static and dynamic lightpath connection requests. The GRWA problem is NP-Complete since it is a generalization of the RWA problem which is known to be NP-Complete. We propose an integer linear programming (ILP) model that accurately depicts the GRWA problem. Because it is very hard to find a solution for large networks using ILP, we solve the GRWA problem by proposing two novel heuristics. The strength of the proposed heuristics stems from their simplicity, efficiency, and applicability to large-scale networks. Our simulation results demonstrate that deploying traffic grooming resources on the edge of optical networks is more cost effective and results in a similar blocking performance to that obtained when distributing the grooming resources throughout the optical network domain.     

OPTIMIZATION OF SPARE CAPACITY IN WDM NETWORKS FOR REAL-TIME SERVICE RESTORATION

In the case of network malfunction a network with restoration capability requires spare capacity to be used. Optimization of the spare capacity in this case is to find the minimum amount of spare capacity for the network to survive from network component failures. In this paper, the optimization of the spare capacity problem is investigated for the wavelength division multiplexing (WDM) mesh networks without wavelength conversion. To minimize the spare capacity, we will optimize both the routing and the wavelength assignment. This combinatorial problem is usually called the routing and wavelength assignment (RWA) problem and it is well known to be NP-hard. We give an integer linear programming (ILP) formulation for the problem. Due to the excessive run-times of the ILP, we propose a hybrid genetic algorithm approach (GA) for the problem. For benchmarking purpose, simulated annealing (SA) and Tabu search (TS) are also applied to this problem. To validate the effectiveness of the proposed method, the approach is applied to the China network, which has a more complicated network topology. Simulation results are very favorable to the GA approach.     

复杂业务需求下的光网络规划问题的研究*

研究了复杂业务需求下的光网络规划问题,建立了支持多种业务需求和保护需求的ILP数学模型;针对大型光网络相应的整数线性模型规模过大、难以求解的困难,引入了Bender数学分解方法。计算结果表明,利用Bender分解可以有效地求解复杂业务需求和保护需求下的光网络规划问题,同时降低时间和内存的消耗。     

Capacitated single allocation hub location problem—A bi-criteria approach

A different approach to the capacitated single allocation hub location problem is presented. Instead of using capacity constraints to limit the amount of flow that can be received by the hubs, we introduce a second objective function to the model (besides the traditional cost minimizing function), that tries to minimize the time to process the flow entering the hubs. Two bi-criteria single allocation hub location problems are presented: in a first model, total time is considered as the second criteria and, in a second model, the maximum service time for the hubs is minimized. To generate non-dominated solutions an interactive decision-aid approach developed for bi-criteria integer linear programming problems is used. Both bi-criteria models are tested on a set of instances, analyzing the corresponding non-dominated solutions set and studying the reasonableness of the hubs flow charge for these non-dominated solutions. The increased information provided by the non-dominated solutions of the bi-criteria model when compared to the unique solution given by the capacitated hub location model is highlighted.     

Multicast protection scheme in survivable WDM optical networks

The protection design is a key issue in survivable wavelength division multiplexing (WDM) optical networks. Most researches focused on protecting unicast traffic against the failure of a single network component such as a link or a node. In this paper, we investigate the protection scheme for multicast traffic in meshed WDM optical networks under dual-link failure consideration, and propose a novel protection algorithm called shared segment protection with reprovisioning (SSPR). Through dynamically adjusting link-cost according to the current network state, SSPR establishes a primary light-tree and corresponding link-disjoint backup segments for each multicast connection request. A backup segment can efficiently share wavelength capacity of its working tree or the common resource of other backup segments. Capacity reprovisioning establishes new segments for the vulnerable connections after a link failure and tolerates following link failures. The simulation results show that SSPR not only can make good use of wavelength resources and protect multicast sessions against any single-link failure, but also can greatly improve the traffic restorability in the event of dual-link breakdown.     

Topology-aware wavelength partitioning for DWDM OBS networks: A novel approach for absolute QoS provisioning

Optical Burst Switching (OBS) is a promising switching technology for the next generation all-optical networks. An OBS network without wavelength converters and fiber delay lines can be implemented simply and cost-effectively using the existing technology. However, this kind of networks suffers from a relatively high burst loss probability at the OBS core nodes. To overcome this issue and consolidate OBS networks with QoS provisioning capabilities, we propose a wavelength partitioning approach, called Optimization-based Topology-aware Wavelength Partitioning approach (OTWP). OTWP formulates the wavelength partitioning problem, based on the topology of the network, as an Integer Linear Programming (ILP) model and uses a tabu search algorithm (TS) to resolve large instances efficiently. We use OTWP to develop an absolute QoS differentiation scheme, called Absolute Fair Quality of service Differentiation scheme (AFQD). AFQD is the first absolute QoS provisioning scheme that guarantees loss-free transmission for high priority traffic, inside the OBS network, regardless of its topology. Also, we use OTWP to develop a wavelength assignment scheme, called Best Effort Traffic Wavelength Assignment scheme (BETWA). BETWA aims to reduce loss probability for best effort traffic. To make AFQD adaptive to non-uniform traffic, we develop a wavelength borrowing protocol, called Wavelength Borrowing Protocol (WBP). Numerical results show the effectiveness of the proposed tabu search algorithm to resolve large instances of the partitioning problem. Also, simulation results, using ns-2, show that: (a) AFQD provides an excellent quality of service differentiation; (b) BETWA substantially decreases the loss probability of best effort traffic to a remarkably low level for the OBS network under study; and (c) WBP makes AFQD adaptive to non-uniform traffic by reducing efficiently blocking probability for high priority traffic.     

Investigation on static routing and resource assignment of elastic all-optical switched intra-datacenter networks基于弹性全光交换技术的数据中心内网的静态路由和资源分配(RSIA)

In this paper, we explore the issue of static routing and spectrum/IT resource assignment (RSIA) of elastic all-optical switched intra-datacenter networks (intra-DCNs) by proposing anycast- and manycast-based integer linear programming (ILP) models. The objective is to jointly optimize the DCN resources, i.e., network transmission bandwidth and IT resources, under different situations. First, for given service-request matrices with unknown network transmission bandwidth and IT resources, we propose anycast and manycast ILP models to minimize the maximum numbers of required network and IT resources to accommodate all the service requests. For anycast RSIA issue, we proposed two different ILP models that are based on node-arc and link-path methods, respectively. Node-arc based manycast ILP model is also proposed for the first time to our knowledge. Second, for given network transmission bandwidth and IT resources and known service-request matrices, we propose node-arc based anycast ILP models to maximize the total number of successfully served service requests. To evaluate the efficiency of anycast and manycast models, all proposed ILP models are evaluated and compared with unicast ILP models. Simulation results show that anycast and manycast ILP models perform much better in efficiently using DCN resources and successfully accommodating more service requests when compared to unicast ILP models under the same network conditions.     

A novel admission control mechanism in GMPLS-based IP over optical networks

With the migration of real-time and high-priority traffic in IP networks, dynamic admission control mechanisms are very important in high-capacity networks where IP and optical technologies have converged with a GMPLS-based control-plane. In this paper proposes, we propose an integrated multilayer traffic engineering framework that considers both physical and logical (optical layer) topologies for dynamically admitting new label switched paths (LSPs) in GMPLS networks. The dynamic admission control mechanism is based on an optimal resolution of an integer linear programming model that takes into account both lightpaths availability, wavelength continuity and routing constraints. In order to minimize LSPs set up delays, this mechanism first considers the logical topology (set of lightpaths) that is already in place before setting up a new lightpath for the incoming LSP, resulting in an additional set up signaling delay. When tested by simulations, results confirm that the proposed formulation effectively improves the network performance by reducing the connection blocking rate, while guaranteeing strict delay and noise constraints.     

Models for the two‐dimensional rectangular single large placement problem with guillotine cuts and constrained pattern

In this paper, we address the constrained two‐dimensional rectangular guillotine single large placement problem (2D_R_CG_SLOPP). This problem involves cutting a rectangular object to produce smaller rectangular items from orthogonal guillotine cuts. In addition, there is an upper limit on the number of copies that can be produced of each item type. To model this problem, we propose a new pseudopolynomial integer nonlinear programming (INLP) formulation and obtain an equivalent integer linear programming (ILP) formulation from it. Additionally, we developed a procedure to reduce the numbers of variables and constraints of the integer linear programming (ILP) formulation, without loss of optimality. From the ILP formulation, we derive two new pseudopolynomial models for particular cases of the 2D_R_CG_SLOPP, which consider only two‐staged or one‐group patterns. Finally, as a specific solution method for the 2D_R_CG_SLOPP, we apply Benders decomposition to the proposed ILP formulation and develop a branch‐and‐Benders‐cut algorithm. All proposed approaches are evaluated through computational experiments using benchmark instances and compared with other formulations available in the literature. The results show that the new formulations are appropriate in scenarios characterized by few item types that are large with respect to the object's dimensions.     

Optimization models and methods for planning wireless mesh networks

In this paper novel optimization models are proposed for planning Wireless Mesh Networks (WMNs), where the objective is to minimize the network installation cost while providing full coverage to wireless mesh clients. Our mixed integer linear programming models allow to select the number and positions of mesh routers and access points, while accurately taking into account traffic routing, interference, rate adaptation, and channel assignment. We provide the optimal solutions of three problem formulations for a set of realistic-size instances (with up to 60 mesh devices) and discuss the effect of different parameters on the characteristics of the planned networks. Moreover, we propose and evaluate a relaxation-based heuristic for large-sized network instances which jointly solves the topology/coverage planning and channel assignment problems. Finally, the quality of the planned networks is evaluated under different traffic conditions through detailed system level simulations.     

软件定义网络中基于网络切片和ILP模型的路由方案

针对软件定义网络(SDN)中数据层的路由优化问题,提出一种基于网络切片和 整数线性规划(ILP) 多约束优化的路由方案。首先,根据多租户业务的链路需求,基于Kruskal算法对数据层中的链路资源进行网络切片,尽可能形成相互隔离的租户子网络。然后,在考虑链路约束和租户业务的服务质量(QoS)约束下, 以最小化传输延迟为目标, 构建一个ILP整数线性规划(ILP)路由优化模型,并获得最佳的路由方案。仿真结果表明,所获得的路由方案具有较少的共享链路,有效降低了链路拥塞和传输延迟。     

Scheduling and variable binding for improved testability in high level synthesis

In this paper, we present a scheduling and a variable binding technique for improved testability in high level synthesis. The scheduling technique called cost based scheduling system (CBSS), is time constrained which minimizes the number of resources (operations) and the number of registers based on a cost function. The CBSS improves the life time of primary input and primary output variables, reduces the life times of intermediate variables and hence improves the controllability and observability. The testability of the register transfer level (RTL) structure generated by this schedule is therefore improved. CBSS considers all the variables and operations jointly for scheduling. CBSS supports various scheduling modes such as multicycled and chained operations, and pipelining. The complexity of our scheduling algorithm is O(c·n²) where c is the number of control steps and n is the number of operations to be scheduled. To generate a highly testable RTL structure, the CBSS is followed by a variable binding technique to bind the variables into registers. An integer linear programming (ILP) approach is proposed with an objective function that minimizes the number of registers and a set of constraints that improves the testability of the RTL structure. Various case studies are presented and the results on different benchmark examples show the potential of our approach.     

A new approach for designing fault-tolerant WDM networks

In recent years, path protection has emerged as a widely accepted technique for designing survivable WDM networks. This approach is attractive, since it is able to provide bandwidth guarantees in the presence of link failures. However, it requires allocating resources for backup lightpaths, which remain idle under normal fault-free conditions. In this paper, we introduce a new approach for designing fault-tolerant WDM networks, based on the concept of survivable routing. Survivable routing of a logical topology ensures that the lightpaths are routed in such a way that a single link failure does not disconnect the network. When a topology is generated using our approach, it is guaranteed to have a survivable routing. We further ensure that the logical topology is able to handle the entire traffic demand after any single link failure. We first present an ILP that optimally designs a survivable logical topology, and then propose a heuristic for larger networks. Experimental results demonstrate that this new approach is able to provide guaranteed bandwidth, and is much more efficient in terms of resource utilization, compared to both dedicated and shared path protection.     

Gamma deployment problem in grids: hardness and new integer linear programming formulation

Vehicular networks are mobile networks designed for the domain of vehicles and pedestrians. These networks are an essential component of intelligent transportation systems and have the potential to ease traffic management, lower accident rates, and offer other solutions to smart cities. One of the most challenging aspects in the design of a vehicular network is the distribution of its infrastructure units, which are called roadside units (RSUs). In this work, we tackle the gamma deployment problem that consists of deploying the minimum number of RSUs in a vehicular network in accordance with a quality of service metric called gamma deployment. This metric defines a vehicle as covered if it connects to some RSUs at least once in a given time interval during its whole trip. Then, the metric parameterizes the minimum percentage of covered vehicles necessary to make a deployment acceptable or feasible. In this paper, we prove that the decision version of the gamma deployment problem in grids is NP‐complete. Moreover, we correct the multiflow integer linear programming formulation present in the literature and introduce a new formulation based on set covering that is at least as strong as the multiflow formulation. In experiments with a commercial solver, the set covering formulation widely outperforms the multiflow formulation with respect to running time and linear programming relaxation gap.     

On the complexity and algorithm of grooming regular traffic in WDM optical networks

In SONET/WDM networks, a high-speed wavelength channel is usually shared by multiple low-rate traffic demands to make efficient use of the wavelength capacity. The multiplexing is known as traffic grooming and performed by SONET Add-Drop Multiplexers (SADM). The maximum number of low-rate traffic demands that can be multiplexed into one wavelength channel is called grooming factor. Since SADMs are expensive, a key optimization goal of traffic grooming is to minimize the total number of SADMs in order to satisfy a given set of traffic demands. As an important communication traffic pattern, all-to-all traffic has been widely studied for the traffic grooming problem. In this paper, we study the regular traffic pattern, which is considered as a generalization of the all-to-all traffic pattern. We focus on the Unidirectional Path-Switched Ring (UPSR) networks. We prove that the traffic grooming problem is NP-hard for the regular traffic pattern in UPSR networks, and show that the problem does not admit a Fully Polynomial Time Approximation Scheme (FPTAS). We further prove that the problem remains NP-hard even if the grooming factor is any fixed value chosen from a subset of integers. We also propose a performance guaranteed algorithm to minimize the total number of required SADMs, and show that the algorithm achieves a better upper bound than previous algorithms. Extensive simulations are conducted, and the empirical results validate that our algorithm outperforms the previous ones in most cases. In addition, our algorithm always uses the minimum number of wavelengths, which are precious resources as well in optical networks.     

Tabu search algorithm for routing,modulation and spectrum allocation in elastic optical network with anycast and unicast traffic

The paper presents a novel method based on the standard tabu search (TS) approach, dedicated to solve the routing, modulation and spectrum allocation (RMSA) problem in elastic optical networks (EONs). The considered formulation of the RMSA problem covers simultaneously unicast (one-to-one) and anycast (one-to-one-of-many) traffic demands. This is a very important issue taking into account the fact that anycasting gains more and more importance in contemporary Internet due the growing popularity of services like cloud computing, content delivery networks, and video streaming. In this paper, we formulate RMSA as an integer linear programming (ILP) problem and we study four different objective functions, which are related to, respectively, cost, power consumption, maximum and average spectrum usage. We evaluate the performance of our TS method based on the comparison with both optimal results yielded by the CPLEX solver and the results obtained by reference heuristic algorithms proposed in the literature. Moreover, we evaluate benefits of the use of anycasting in EONs. The performed simulation experiments demonstrate that the proposed algorithm outperforms other reference methods. What is more, we show that the anycast transmission can provide significant savings compared to the typical unicast transmission.     

An integer linear programming-based tool for wireless sensor networks

Wireless sensor networks will be widely deployed in the future for monitoring important environmental conditions, security, and health care. One of the most important challenges in the implementation of such networks is minimizing energy dissipation. Given that many of the energy optimization problems defined for sensor networks are very hard, heuristics are commonly employed. Evaluating the effectiveness of these heuristics, i.e., how close do they come to the optimal solutions, is a challenge. While algorithms that give optimal solutions cannot be on-line (since they are expensive), if they are used off-line, they can provide invaluable insight to improve existing heuristics and to derive new ones. In this paper, we present an integer linear programming (ILP)-based tool that can be used to evaluate optimal solutions for communication energy optimization in sensor networks under specific constraints. This tool, which is based on the required sensing and communication schedules, determines optimal sensor movement and communication strategies to minimize energy consumption due to inter-sensor communication. The tool can also accommodate several constraints related to movement capabilities of sensor nodes, their battery capacities, and their communication ranges since all these can be expressed in a linear form. In addition, it can also work with objective functions other than minimizing communication energy. Our experience with the tool indicates that it is very useful for studying different scenarios under which an objective function needs to be optimized.     

Differentiated survivability with improved fairness in IP/MPLS-over-WDM optical networks

This paper addresses the priority-fairness problem inherent in provisioning differentiated survivability services for sub-lambda connections associated with different protection-classes in IP/MPLS-over-WDM networks. The priority-fairness problem arises because, high-priority connections requiring high quality of protection such as lambda level pre-configured lightpath protection are more likely to be rejected when compared to low-priority connections which may not need such a high quality of protection. A challenging task in addressing this problem is that, while improving the acceptance rate of high-priority connections, low-priority connections should not be over-penalized. We propose two solution-approaches to address this problem. In the first approach, a new inter-class backup resource sharing (ICBS) technique and a differentiated routing scheme (DiffRoute) are adopted. The ICBS is investigated in two methods: partial- and full-ICBS (p-ICBS and f-ICBS) methods. The DiffRoute scheme uses different routing criteria for the traffic classes. In the second approach, two rerouting schemes are developed. The rerouting schemes are applied with the DiffRoute and ICBS. The rerouting schemes employ inter-layer backup resource sharing and inter-layer primary-backup multiplexing for the benefit of high-priority connections, thus improving fairness. Our findings are as follows. (1) The application of p-ICBS and DiffRoute yields improved performance for high-priority connections. However, it shows penalized performance for low-priority connections. On the other hand, the collective application of f-ICBS and DiffRoute yields significantly improved performance for high-priority connections with no penalized performance as the performance of low-priority connections is also improved. (2) The rerouting schemes, when applied with the DiffRoute and ICBS methods, further improve the performance of high-priority traffic without significantly affecting the performance of other traffic.     

一种稀疏波长转换光网络中的波长分配算法

研究了具有波长转换功能的WDM光网络的分类以及已有的几种波长分配算法,分析了波长分配算法的一般流程。文中以波长变换次数最少做为所提出的波长分配算法的主要优化目标,根据WDM光网络中的节点是否具有波长转换的功能,结合等价光路由替换的思想,提出了在稀疏有限波长转换光网络中的一种启发式的波长分配算法。仿真实验表明,当光网络中的连接请求量较大时,该算法的阻塞率低于已有的一些波长分配算法,连接能力有了较大提高。     

Ant colony optimization for dynamic routing and wavelength assignment in WDM networks with sparse wavelength conversion

Since optical WDM networks are becoming one of the alternatives for building up backbones, dynamic routing, and wavelength assignment with delay constraints (DRWA-DC) in WDM networks with sparse wavelength conversions is important for a communication model to route requests subject to delay bounds. Since the NP-hard minimum Steiner tree problem can be reduced to the DRWA-DC problem, it is very unlikely to derive optimal solutions in a reasonable time for the DRWA-DC problem. In this paper, we circumvent to apply a meta-heuristic based upon the ant colony optimization (ACO) approach to produce approximate solutions in a timely manner. In the literature, the ACO approach has been successfully applied to several well-known combinatorial optimization problems whose solutions might be in the form of paths on the associated graphs. The ACO algorithm proposed in this paper incorporates several new features so as to select wavelength links for which the communication cost and the transmission delay of routing the request can be minimized as much as possible subject to the specified delay bound. Computational experiments are designed and conducted to study the performance of the proposed algorithm. Comparing with the optimal solutions found by an ILP formulation, numerical results evince that the ACO algorithm is effective and robust in providing quality approximate solutions to the DRWA-DC problem.